ANALISIS KEPUASAN KONSUMEN PADA PENERAPAN PEMASARAN DIGITAL UNTUK KOMODITAS PETERNAKAN
Bibliographic record
Abstract
The Covid-19 pandemic had a significant impact on livestock businesses and SMEs processing derivative products from cattle, goats, and sheep with a decrease in sales levels, along with the decline in people's purchasing power. This is evidenced by the low level of household consumption which only grew by 2.84% in the first quarter of 2019-2020 compared to the first quarter of 2018-2019 which reached 5.020. This condition is very influential on the sustainability of SME business.The development of marketing strategies is one of the alternative solutions that are expected to help farmers and SMEs entrepreneurs in the processed of derivative products to survive and develop their business. Not stopping at the application of digital marketing application only, research on measuring the consumer satisfaction index is also carried out related to the products marketed and the use of digital marketing applications is expected to help obtained information related to the marketing goals to be achieved and find out the amount of consumer satisfaction index resulting from services that have been provided and products consumed. The research that using the Customer Satisfaction Index (CSI) analysis method showed a consumer satisfaction value index of 80.523% which has meaning that consumer has already feel satisfied. Among the attributes that has been tested showed the highest satisfaction values were product taste (86.0%), price (85.33%) while those attributes that needed to be improved performance were on size variations (72.67%) and promotions (74.0%). ABSTRAKPandemi Covid 19 berdampak cukup signifikan bagi usaha peternakan dan UKM pengolah produk turunan dari sapi, kambing, dan domba dengan penurunan tingkat penjualan, seiring dengan penurunan daya beli masyarakat. Hal ini dibuktikan dengan rendahnya tingkat konsumsi rumah tangga yang hanya tumbuh 2,84% pada triwulan I tahun 2019-2020 dibandingkan triwulan I tahun 2018-2019 yang mencapai angka 5,02. Hal ini tentu saja sangat berpengaruh terhadap keberlangsungan usaha UKM. Pengembangan strategi pemasaran menjadi salah satu alternatif solusi yang diharapkan mampu membantu para peternak dan pengusaha UKM bidang olahan produk turunan ini untuk tetap dapat bertahan dan mengembangkan usahanya. Tidak berhenti pada aplikasi penerapan pemasaran digital saja, penelitian mengenai pengukuran terhadap indeks kepuasan konsumen juga dilakukan berkaitan dengan produk yang dipasarkan dan penggunaan aplikasi digital marketing ini diharapkan dapat membantu memperoleh informasi terkait sasaran pemasaran yang ingin dicapai serta mengetahui besaran indeks kepuasan konsumen yang dihasilkan dari layanan yang telah diberikan dan produk yang dikonsumsi. Penelitian yang menggunakan metode analisis Customer Satisfaction Index (CSI) ini menunjukkan indeks nilai kepuasan konsumen sebesar 80,523% yang menunjukkan bahwa rata-rata konsumen telah merasa puas. Diantara atribut-atribut yang diuji yang menunjukkan nilai kepuasan tertinggi adalah rasa (86,0%), harga (85,33%) sementara yang perlu ditingkatkan kinerjanya adalah pada variasi ukuran (72,67%) dan promosi (74,0%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".